Grigorios Tsoumakas – författare

The ever expanding abundance of information and computing power enables - searchers and users to tackle highly interesting issues, such as applications prov- ing personalized access and interactivity to multimodal information based on user preferences and semantic concepts or human-machine interface systems utilizing information on the affective state of the user. The general focus of the AIAI conf- ence is to provide insights on how AI can be implemented in real world applications. This volume contains papers selected for presentation at the 5th IFIP Conf- ence on Artificial Intelligence Applications & Innovations (AIAI 2009) being held from 23rd till 25th of April, in Thessaloniki, Greece. The IFIP AIAI 2009 conf- ence is co-organized by the Aristotle University of Thessaloniki, by the University of Macedonia Thessaloniki and by the Democritus University of Thrace. AIAI 2009 is the official conference of the WG12.5 "Artificial Intelligence Appli- tions" working group of IFIP TC12 the International Federation for Information Processing Technical Committee on Artificial Intelligence (AI). It is a conference growing and maintaining high standards of quality. The p- pose of the 5th IFIP AIAI Conference is to bring together researchers, engineers and practitioners interested in the technical advances and business / industrial - plications of intelligent systems. AIAI 2009 is not only focused in providing - sights on how AI can be implemented in real world applications, but it also covers innovative methods, tools and ideas of AI on architectural and algorithmic level.

The ever expanding abundance of information and computing power enables - searchers and users to tackle highly interesting issues, such as applications prov- ing personalized access and interactivity to multimodal information based on user preferences and semantic concepts or human-machine interface systems utilizing information on the affective state of the user. The general focus of the AIAI conf- ence is to provide insights on how AI can be implemented in real world applications. This volume contains papers selected for presentation at the 5th IFIP Conf- ence on Artificial Intelligence Applications & Innovations (AIAI 2009) being held from 23rd till 25th of April, in Thessaloniki, Greece. The IFIP AIAI 2009 conf- ence is co-organized by the Aristotle University of Thessaloniki, by the University of Macedonia Thessaloniki and by the Democritus University of Thrace. AIAI 2009 is the official conference of the WG12.5 "Artificial Intelligence Appli- tions" working group of IFIP TC12 the International Federation for Information Processing Technical Committee on Artificial Intelligence (AI). It is a conference growing and maintaining high standards of quality. The p- pose of the 5th IFIP AIAI Conference is to bring together researchers, engineers and practitioners interested in the technical advances and business / industrial - plications of intelligent systems. AIAI 2009 is not only focused in providing - sights on how AI can be implemented in real world applications, but it also covers innovative methods, tools and ideas of AI on architectural and algorithmic level.

This book constitutes the proceedings of the 23rd International Conference on Discovery Science, DS 2020, which took place during October 19-21, 2020. The conference was planned to take place in Thessaloniki, Greece, but had to change to an online format due to the COVID-19 pandemic.

The multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022.The 236 full papers presented in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions.The volumes are organized in topical sections as follows:Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning; Part II: Networks and graphs; knowledge graphs; social network analysis; graph neural networks; natural language processing and text mining; conversational systems; Part III: Deep learning; robust and adversarial machine learning; generative models; computer vision; meta-learning, neural architecture search; Part IV: Reinforcement learning; multi-agent reinforcement learning; bandits and online learning; active and semi-supervised learning; private and federated learning; .Part V: Supervised learning; probabilistic inference; optimal transport; optimization; quantum, hardware; sustainability; Part VI: Time series; financial machine learning; applications; applications: transportation; demo track.

Chapters “On the Current State of Reproducibility and Reporting of Uncertainty for Aspect-Based SentimentAnalysis” and “Contextualized Graph Embeddings for Adverse Drug Event Detection” are licensed under theterms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/). For further details see license information in the chapter.

The multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022.The 236 full papers presented in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions.The volumes are organized in topical sections as follows:Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning; Part II: Networks and graphs; knowledge graphs; social network analysis; graph neural networks; natural language processing and text mining; conversational systems; Part III: Deep learning; robust and adversarial machine learning; generative models; computer vision; meta-learning, neural architecture search; Part IV: Reinforcement learning; multi-agent reinforcement learning; bandits and online learning; active and semi-supervised learning; private and federated learning; .Part V: Supervised learning; probabilistic inference; optimal transport; optimization; quantum, hardware; sustainability; Part VI: Time series; financial machine learning; applications; applications: transportation; demo track.

The multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022.The 236 full papers presented in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions.The volumes are organized in topical sections as follows:Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning; Part II: Networks and graphs; knowledge graphs; social network analysis; graph neural networks; natural language processing and text mining; conversational systems; Part III: Deep learning; robust and adversarial machine learning; generative models; computer vision; meta-learning, neural architecture search; Part IV: Reinforcement learning; multi-agent reinforcement learning; bandits and online learning; active and semi-supervised learning; private and federated learning;Part V: Supervised learning; probabilistic inference; optimal transport; optimization; quantum, hardware; sustainability; Part VI: Time series; financial machine learning; applications; applications: transportation; demo track.

The multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022.The 236 full papers presented in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions.The volumes are organized in topical sections as follows:Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning; Part II: Networks and graphs; knowledge graphs; social network analysis; graph neural networks; natural language processing and text mining; conversational systems; Part III: Deep learning; robust and adversarial machine learning; generative models; computer vision; meta-learning, neural architecture search; Part IV: Reinforcement learning; multi-agent reinforcement learning; bandits and online learning; active and semi-supervised learning; private and federated learning; .Part V: Supervised learning; probabilistic inference; optimal transport; optimization; quantum, hardware; sustainability; Part VI: Time series; financial machine learning; applications; applications: transportation; demo track.